Triple
T3391753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States bankruptcy law |
E71435
|
entity |
| Predicate | includesChapter |
P6720
|
FINISHED |
| Object | Chapter 7 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Chapter 7 | Statement: [United States bankruptcy law, includesChapter, Chapter 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesChapter Context triple: [United States bankruptcy law, includesChapter, Chapter 7]
-
A.
containsChapter
chosen
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
containsSubchapter
Indicates that one chapter or section includes another, more specific subchapter as a part of its structure.
-
C.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
D.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
E.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb850594c81909b6f8a384fc98cb2 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.